Catalyzing NTD gender and equity research: A call for papers
Bibliographic record
Abstract
Neglected tropical disease (NTD) programs are among the largest community-based public health interventions in existence.More than 1 billion people were reached with preventive chemotherapy for at least one NTD in 2016 alone [1].The significance of the NTD program is predicated upon the opportunity to treat disease, prevent morbidity and disability, and ultimately interrupt infection transmission among large populations.Additionally, the untapped potential of these programs lies in the possibility of reaching hard-to-reach individuals with additional health services that may otherwise be inaccessible to them due to a myriad of geographic, social, or cultural obstacles.NTDs disproportionality affect socially and economically marginalized populations globally, and by virtue, NTD programs can provide invaluable healthcare access opportunities for individuals or groups of individuals who are otherwise disenfranchised or isolated.There is a need to build on existing NTD platforms to ensure that these opportunities are available to all individuals regardless of their geographic and social positioning.Accordingly, coverage of NTD interventions has also been proposed as an "equity" tracer within the 2030 Sustainable Development Goals (SDGs) [2].As also emphasized in the 2030 Agenda for Sustainable Development, gender roles and relations-and the ways in which they interact with other intersecting inequities-are often at the heart of inadequate healthcare delivery or access.For NTDs, sex and gender roles can have a profound effect on healthcare access, health outcomes, and caregiver responsibilities [3].There is evidence that NTDs influence adverse birth outcomes for pregnant women and women of reproductive age, resulting in chronic anemia, premature birth, and even increased risk of maternal mortality [4,5].Likewise, women infected with some NTDs may face a disproportionate risk of acquiring sexually transmitted infections such as HIV [6], or social exclusion and stigma if they develop NTD-associated morbidities and disability [7,8].Risk of NTD infection may also be gendered, often based upon social differentiation of occupational and household tasks [9,10].Importantly, gender also intersects with other axes of inequity such as ethnicity, socioeconomic status, occupation status, age, sexuality, (dis)ability, or religion, and there is increasing interest in gender and intersectionality analysis to address key global health priority issues [11].For example, gender norms can affect the ability of women to participate as community volunteers in preventive chemotherapy programs due to the influence of
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.017 | 0.022 |
| Insufficient payload (model declined to judge) | 0.086 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".